[](http://navis.readthedocs.io/en/latest/?badge=latest) [](https://github.com/navis-org/navis/actions/workflows/test-package.yml) [](https://github.com/navis-org/navis/actions/workflows/notebooktest-package.yml) [](https://colab.research.google.com/github/navis-org/navis/blob/master/examples/colab.ipynb) [](https://zenodo.org/doi/10.5281/zenodo.4699382) [](https://pepy.tech/project/navis)
<img src="https://github.com/navis-org/navis/raw/master/docs/_static/logo_new.png" height="150">
NAVis is a Python 3 library for **N**euron **A**nalysis and **Vis**ualization.
## Documentation
NAVis is on [ReadTheDocs](http://navis.readthedocs.io/ "NAVis ReadTheDocs").
## Features
* **polyglot**: work and convert between neuron skeletons, meshes, dotprops and images
* **visualize**: 2D (matplotlib) and 3D (vispy, plotly or k3d)
* **process**: skeletonization, meshing, smoothing, repair, downsampling, etc.
* **morphometrics**: Strahler analysis, cable length, volume, tortuosity and more
* **similarity**: compare & cluster by morphology (e.g. NBLAST, persistence or form factor) or connectivity metrics
* **transform**: move data between template brains (built-in support for HDF5, CMTK, Elastix and landmark-based transforms)
* **interface**: load neurons directly from [neuPrint](https://neuprint.janelia.org), [neuromorpho.org](http://neuromorpho.org) and other data sources
* **model** neurons and networks using the *NEURON* simulator
* **render**: use Blender 3D for high quality [visualizations](https://youtu.be/wl3sFG7WQJc)
* **R** neuron libraries: interfaces with [nat](https://github.com/jefferis/nat), [rcatmaid](https://github.com/jefferis/rcatmaid), [elmr](https://github.com/jefferis/elmr) and more
* **import-export**: read/write SWCs, neuroglancer's ["*precomputed*"](https://github.com/google/neuroglancer/tree/master/src/neuroglancer/datasource/precomputed) format, NMX/NML, NRRD, mesh-files and more
* **scalable**: out-of-the-box support for multiprocessing
* **extensible**: build your own package on top of navis - see [pymaid](https://pymaid.readthedocs.io/en/latest/) for example
## Getting started
See the [documentation](http://navis.readthedocs.io/ "NAVis ReadTheDocs") for detailed installation instructions, tutorials and examples. For the impatient:
```sh
pip3 install 'navis[all]'
```
which includes all optional extras providing features and/or performance improvements.
Currently, this is
`igraph`,
`pathos`,
`shapely`,
`kdtree`,
`hash`,
`flybrains`,
`cloudvolume`,
`meshes`,
and `vispy-default`.
3D plotting from a python REPL is provided by `vispy`, which has a choice of backends.
Different backends work best on different combinations of hardware, OS, python distribution, and REPL, so there may be some trial and error involved.
`vispy`'s backends are [listed here](https://vispy.org/installation.html#backend-requirements), and each can be installed as a navis extra, e.g. `pip3 install 'navis[vispy-pyqt6]'`.
## Questions?
Questions on how to use `navis` are best placed in [discussions](https://github.com/navis-org/navis/discussions). Same goes for cool projects or analyses you made using `navis` -
we'd love to hear from you!
## Changelog
A summary of changes can be found
[here](https://navis.readthedocs.io/en/latest/source/whats_new.html).
## NAVis & friends
<p align="center">
<img src="https://github.com/navis-org/navis/blob/master/docs/_static/navis_ecosystem.png?raw=true" width="700">
</p>
NAVis comes with batteries included but is also highly extensible. Some
libraries built on top of NAVis:
* [flybrains](https://github.com/navis-org/navis-flybrains) provides templates and transforms for *Drosophila* brains to use with navis
* [pymaid](https://pymaid.readthedocs.io/en/latest/) pulls and pushes data from/to CATMAID servers
* [fafbseg](https://fafbseg-py.readthedocs.io/en/latest/index.html) contains tools to work with auto-segmented data for the FAFB EM dataset including FlyWire
## Who uses NAVis?
NAVis has been used in a range of neurobiological publications. See [here](publications.md) for a list.
We have implemented various published algorithms and methods:
1. NBLAST: Comparison of neurons based on morphology [(Costa et al., 2016)](https://www.cell.com/neuron/fulltext/S0896-6273(16)30265-3?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0896627316302653%3Fshowall%3Dtrue)
2. Vertex Similarity: Comparison of neurons based on connectivity [(Jarrell et al., 2012)](http://science.sciencemag.org/content/337/6093/437.long)
3. Comparison of neurons based on synapse distribution
[(Schlegel et al., 2016)](https://elifesciences.org/content/5/e16799)
4. Synapse flow centrality for axon-dendrite splits [(Schneider-Mizell et al., 2016)](https://elifesciences.org/articles/12059)
Working on your own cool new method? Consider adding it to NAVis!
## Citing NAVis
We'd love to know if you found NAVis useful for your research! You can help us
spread the word by citing the DOI provided by Zenodo [](https://zenodo.org/doi/10.5281/zenodo.4699382)
## License
This code is under [GNU GPL V3](LICENSE).
## Acknowledgments
NAVis is inspired by and inherits much of its design from the excellent
[natverse](http://natverse.org) R packages by
[Greg Jefferis](https://github.com/jefferis), [Alex Bates](https://github.com/alexanderbates),
[James Manton](https://github.com/ajdm) and others.
## Contributing
Want to contribute? Great, here is how!
#### Report bugs or request features
Open an [issue](https://github.com/navis-org/navis/issues). For bug reports
please make sure to include some code/data with a minimum example for us to
reproduce the bug.
#### Contribute code
We're always happy for people to contribute code - be it a small bug fix, a
new feature or improved documentation.
Here's how you'd do it in a nutshell:
1. Fork this repository
2. `git clone` it to your local machine
3. Install the full development dependencies with `pip install -r requirements.txt`
4. Install the package in editable mode with `pip install -e ".[all]"`
5. Create, `git add`, `git commit`, `git push`, and pull request your changes.
Run the tests locally with `pytest -v`.
Docstrings should use the [numpydoc](https://numpydoc.readthedocs.io/en/latest/format.html) format,
and make sure you include any relevant links and citations.
Unit tests should be [doctests](https://docs.python.org/3/library/doctest.html)
and/or use [pytest](https://docs.pytest.org/en/stable/) in the `./tests` directory.
Doctests have access to the `tmp_dir: pathlib.Path` variable,
which should be used if any files need to be written.
Feel free to get in touch either through an [issue](https://github.com/navis-org/navis/issues)
or [discussion](https://github.com/navis-org/navis/discussions) if you need
pointers or input on how to implement an idea.
Raw data
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"description": "[](http://navis.readthedocs.io/en/latest/?badge=latest) [](https://github.com/navis-org/navis/actions/workflows/test-package.yml) [](https://github.com/navis-org/navis/actions/workflows/notebooktest-package.yml) [](https://colab.research.google.com/github/navis-org/navis/blob/master/examples/colab.ipynb) [](https://zenodo.org/doi/10.5281/zenodo.4699382) [](https://pepy.tech/project/navis)\n\n<img src=\"https://github.com/navis-org/navis/raw/master/docs/_static/logo_new.png\" height=\"150\">\n\nNAVis is a Python 3 library for **N**euron **A**nalysis and **Vis**ualization.\n\n## Documentation\nNAVis is on [ReadTheDocs](http://navis.readthedocs.io/ \"NAVis ReadTheDocs\").\n\n## Features\n* **polyglot**: work and convert between neuron skeletons, meshes, dotprops and images\n* **visualize**: 2D (matplotlib) and 3D (vispy, plotly or k3d)\n* **process**: skeletonization, meshing, smoothing, repair, downsampling, etc.\n* **morphometrics**: Strahler analysis, cable length, volume, tortuosity and more\n* **similarity**: compare & cluster by morphology (e.g. NBLAST, persistence or form factor) or connectivity metrics\n* **transform**: move data between template brains (built-in support for HDF5, CMTK, Elastix and landmark-based transforms)\n* **interface**: load neurons directly from [neuPrint](https://neuprint.janelia.org), [neuromorpho.org](http://neuromorpho.org) and other data sources\n* **model** neurons and networks using the *NEURON* simulator\n* **render**: use Blender 3D for high quality [visualizations](https://youtu.be/wl3sFG7WQJc)\n* **R** neuron libraries: interfaces with [nat](https://github.com/jefferis/nat), [rcatmaid](https://github.com/jefferis/rcatmaid), [elmr](https://github.com/jefferis/elmr) and more\n* **import-export**: read/write SWCs, neuroglancer's [\"*precomputed*\"](https://github.com/google/neuroglancer/tree/master/src/neuroglancer/datasource/precomputed) format, NMX/NML, NRRD, mesh-files and more\n* **scalable**: out-of-the-box support for multiprocessing\n* **extensible**: build your own package on top of navis - see [pymaid](https://pymaid.readthedocs.io/en/latest/) for example\n\n## Getting started\nSee the [documentation](http://navis.readthedocs.io/ \"NAVis ReadTheDocs\") for detailed installation instructions, tutorials and examples. For the impatient:\n\n```sh\npip3 install 'navis[all]'\n```\n\nwhich includes all optional extras providing features and/or performance improvements.\nCurrently, this is\n`igraph`,\n`pathos`,\n`shapely`,\n`kdtree`,\n`hash`,\n`flybrains`,\n`cloudvolume`,\n`meshes`,\nand `vispy-default`.\n\n3D plotting from a python REPL is provided by `vispy`, which has a choice of backends.\nDifferent backends work best on different combinations of hardware, OS, python distribution, and REPL, so there may be some trial and error involved.\n`vispy`'s backends are [listed here](https://vispy.org/installation.html#backend-requirements), and each can be installed as a navis extra, e.g. `pip3 install 'navis[vispy-pyqt6]'`.\n\n\n\n## Questions?\nQuestions on how to use `navis` are best placed in [discussions](https://github.com/navis-org/navis/discussions). Same goes for cool projects or analyses you made using `navis` -\nwe'd love to hear from you!\n\n## Changelog\n\nA summary of changes can be found\n[here](https://navis.readthedocs.io/en/latest/source/whats_new.html).\n\n## NAVis & friends\n<p align=\"center\">\n<img src=\"https://github.com/navis-org/navis/blob/master/docs/_static/navis_ecosystem.png?raw=true\" width=\"700\">\n</p>\n\nNAVis comes with batteries included but is also highly extensible. Some\nlibraries built on top of NAVis:\n* [flybrains](https://github.com/navis-org/navis-flybrains) provides templates and transforms for *Drosophila* brains to use with navis\n* [pymaid](https://pymaid.readthedocs.io/en/latest/) pulls and pushes data from/to CATMAID servers\n* [fafbseg](https://fafbseg-py.readthedocs.io/en/latest/index.html) contains tools to work with auto-segmented data for the FAFB EM dataset including FlyWire\n\n## Who uses NAVis?\nNAVis has been used in a range of neurobiological publications. See [here](publications.md) for a list.\n\nWe have implemented various published algorithms and methods:\n\n1. NBLAST: Comparison of neurons based on morphology [(Costa et al., 2016)](https://www.cell.com/neuron/fulltext/S0896-6273(16)30265-3?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0896627316302653%3Fshowall%3Dtrue)\n2. Vertex Similarity: Comparison of neurons based on connectivity [(Jarrell et al., 2012)](http://science.sciencemag.org/content/337/6093/437.long)\n3. Comparison of neurons based on synapse distribution\n[(Schlegel et al., 2016)](https://elifesciences.org/content/5/e16799)\n4. Synapse flow centrality for axon-dendrite splits [(Schneider-Mizell et al., 2016)](https://elifesciences.org/articles/12059)\n\nWorking on your own cool new method? Consider adding it to NAVis!\n\n## Citing NAVis\nWe'd love to know if you found NAVis useful for your research! You can help us\nspread the word by citing the DOI provided by Zenodo [](https://zenodo.org/doi/10.5281/zenodo.4699382)\n\n## License\nThis code is under [GNU GPL V3](LICENSE).\n\n## Acknowledgments\nNAVis is inspired by and inherits much of its design from the excellent\n[natverse](http://natverse.org) R packages by\n[Greg Jefferis](https://github.com/jefferis), [Alex Bates](https://github.com/alexanderbates),\n[James Manton](https://github.com/ajdm) and others.\n\n## Contributing\nWant to contribute? Great, here is how!\n\n#### Report bugs or request features\nOpen an [issue](https://github.com/navis-org/navis/issues). For bug reports\nplease make sure to include some code/data with a minimum example for us to\nreproduce the bug.\n\n#### Contribute code\nWe're always happy for people to contribute code - be it a small bug fix, a\nnew feature or improved documentation.\n\nHere's how you'd do it in a nutshell:\n\n1. Fork this repository\n2. `git clone` it to your local machine\n3. 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